Book

Description

In today's competitive job market, efficient talent acquisition is critical for organizations. This project presents an automated approach to streamline hiring processes by leveraging BERT and GPT-3 models. The system begins by analyzing user-provided job descriptions to extract required skills for specific roles, creating a skill vector for comparison. Resumes are then processed, and cosine similarity between the job description and each resume determines skill alignment. BERT enhances this analysis, yielding refined skill alignment scores. Candidates are ranked based on these scores. In today's competitive job market, efficient talent acquisition is critical for organizations. This project presents an automated approach to streamline hiring processes by leveraging BERT and GPT-3 models. The system begins by analyzing user-provided job descriptions to extract required skills for specific roles, creating a skill vector for comparison. Resumes are then processed, and cosine similarity between the job description and each resume determines skill alignment. BERT enhances this analysis, yielding refined skill alignment scores. Candidates are ranked based on these scores. To facilitate screening, the system generates interview questions using GPT-3, covering both qualitative and quantitative skills. This approach enhances the efficiency and objectivity of candidate evaluation, reducing manual effort and bias. By leveraging advanced language models, the system ensures consistent and standardized assessments, giving companies a competitive edge in identifying top talent while providing candidates with a fair evaluation process.